As long as both companies remain stable and viable, there's probably limited upside to pouring more money into them. If they fail, and bring down the AI ecosystem with them, that is very bad news for Nvidia. So they've been there nurturing their success and providing capital to backstop their exponential growth.
You can see Nvidia stepping in throughout the ecosystem with confidence boosting investments where needed. They haven't just supported Anthropic and OpenAI.
If OpenAI and Anthropic succeed, and get their business fly-wheels fully spinning, they don't necessarily need more capital from Huang. Ultimately the goal of Nvidia is to profit from their long-term success by selling them GPUs for a long, long time. The goal isn't to keep plowing money into them forever.
These days Nvidia has more money than it knows what to do with. They could certainly push $5b+ into each company annually and never miss it. They're tracking toward an astounding $200b in operating income (maybe over the next four quarters if the music doesn't suddenly stop).
Why would paying dividends not be like throwing money away for Nvidia, considering the alternative is to reinvest it into Nvidia's R&D, hiring & training, etc. Investors are already happily making money on NVDA stock appreciation, so what more would they gain from paying dividends?
It did not raise $110 billion. According to their own SEC filings $35 billion of Amazon’s funding is contingent on “(i) OpenAI meeting specified milestones, and (ii) OpenAI directly or indirectly consummating an initial public offering or direct listing of equity securities in the United States”
> I can hardly believe that this is legal. They’re basically committing money that doesn’t exist just yet.
What do you mean "just yet" :-)
I don't really know how likely it is that the money being committed will actually exist when the time comes (Softbank's commitment didn't exist, they had to sell off assets and rope in other investors to meet their commitments).
Maybe it is very likely to exist, but, really, who knows?
IOW, your statement would be equally true by ending the sentence at the word "exist".
Vault cash are actual bills in vaults. It doesn't even include the bills in your wallet or under your mattress.
It's small because few people go to the bank to withdraw a suitcase of $100 bills, it's a weird time series to pull up because it's not really indicative of anything outside of narrow interests for regulators and the mint - it's probably some conspiracy theory trope from crypto bros or something.
Most money exists purely in electronic form these days.
Monetary base [0] which includes the digital money banks have on deposit at the Fed, is over $5 trillion, and even that is tiny compared to M1 [1] which includes the kinds of things backing your money market account, which is around $19T.
When money is invested, they're going to wire it, not pull up with wheelbarrows full of bills.
GP is wrong though, vault cash is the incorrect time series for that.
GP should have used Monetary Base if they wanted to consider purely electronic cash (that is not a result of any fractional reserve stuff at all), which is over $5T disproving their point.
That's what I was referring to. They're committing money they don't have in any monetary form at all. They're just promising they'll have it when it comes due. This is kind of like MLM.
> Nvidia CEO Jensen Huang said his company’s recent investments in OpenAI and Anthropic are likely to be its last in both, saying that once they go public as anticipated later this year, the opportunity to invest closes
ok, sounds obvious
> Nvidia, for its part, isn’t offering much more on the matter
ok, so no more news from nvidia
> Still, a few other dynamics might also explain the pullback..
Instead of pouring more money into OpenAI and Anthropic, Nvidia should invest more in expanding production capacity for the RTX 5000 series and future generations. High-end consumer GPU availability is still constrained, especially for the RTX 5090, and street prices remain elevated. Nvidia should come back to the consumer side.
Datacenter income for nVidia last quarter was something like 62B vs the gaming market of <4B. While not quite a rounding error, it feels like the gaming market is just too small for them to put more resources toward it for us consumer folks.
One strategic reason is to remove oxygen from competitors. Otherwise someone will scoop up the gaming market and put the proceeds into developing technology to compete with NVIDIA in the more lucrative AI space.
I wonder who is going to fill the gaming market if AI market focused companies would simply outbid them during manufacturing? All available and not yet available manufacture is pivoting to AI market
“I wouldn’t pick up $20 if there was $100 on the ground!”
Most people would pick up both.
These economic proclamations don’t seem to make sense, when applied to different contexts — which suggests what you’re saying might be folk wisdom rather than sound theory (and greatly over simplifying the problem).
You’re also discounting ecosystem effects — gaming GPUs driving demand for datacenter and workstation GPUs as hobbyist experimentation turns into industrial usage. We don’t know what would happen if nVidia stopped suppressing the GPU market, because it’s never been tried — nVidia has always viciously undercut their own grassroots.
> “I wouldn’t pick up $20 if there was $100 on the ground!” Most people would pick up both.
No, it’s more like there’s a massive pile of both $20s and $100s on the ground. You wouldn’t waste time running between the two, you’d focus on the $100s
if you're within reach of both, then it's not a choice, and there's no opportunity cost in picking just one - you'd be taking both.
If not within reach of both but just one, and you picking one up means someone else might pick up the other, then which would you choose? The other is then by definition, the opportunity cost.
cash cannot buy more fabs. ASML machines are the constraint, plus TSMC's capacity is a constraint.
Not to mention that nvidia's cash pile isn't magic - they should not overpay for capacity; they're better off returning cash to investors in that case.
You’re standing on a traffic island in the middle of a busy road. The lights change allowing you to cross. On one side there is a $20 note, on the other there is a $100 note. Which side do you go to first?
I wouldn't pick up either even with empty hands. No idea where they've been. Maybe a fiver, a twenty sure. At that point I'd put down my bags and grab both.
But so many gamers want to buy GPUs and can’t because they are sold out or won’t because they are super price inflated. Wouldn’t the gaming market be larger if the products were actually available and at their actual MSRP?
Nvidia can't sell 10x the number of GPUs they sell. As much as the supply issues are discussed, it would likely take them a long time to just double the market. They could try to become the vendor of choice for the PS6/next xbox, but that's a big strategy shift for again maybe double the market, not 10x the market.
On the other hand right now the market doesn't seem to think that the >60bn of datacenter revenue is going away or even going to slow down _growing_ any time soon. Just adding 10% more revenue there is worth more than doubling their GPU business which they likely can't do.
I am not saying it would be anywhere near equal, just that it would be "bigger" than 4B if it wasn't so constrained.
>On the other hand right now the market doesn't seem to think that the >60bn of datacenter revenue is going away or even going to slow down _growing_ any time soon.
That is not substantiable. AI bubble is wealthy hype like a single drop of blood can be used to validate 100 different diagnostic test. Reality is parts per million fails this along with reusable medium. Wealth latches to idiocy.
Gaming and CAD market are real expectations that latch to reality. Grow the education systems and grow both. So is matrix math, such as hashing.
AI has reached a state of software issue, not hardware. And the divergence of AI hardware does not equate to CAD and Gaming math.
How many of the last ten years have had some kind of "temporary" GPU shortage? It was crypto, now it's LLMs, who knows what's next?
The only winning strategy for these guys is to exploit the market for all it's worth during shortages and carefully control production to manage the inevitable gluts.
> AI has reached a state of software issue, not hardware
Citation very much needed.
At the very least, OpenAI seems to believe more and larger datacenters is the path to better models... and they've been right about that every time so far.
Slop is still slop. There is no legitimate evidence that these systems get any better just by throwing more hardware at it. Every one of the people in this paper is involved with OpenAI, so it is very suspect in its findings.
I am afriad thhe GPUs chips will be often useless (to power hungry, running too hot and needing too expensive accessories) but it might be possible to harvest the memory chips and put them on useful GPU cards.
Why would they do that? They launched the DGX Spark last year with multiple hardware OEMs selling flavors of the reference device (Dell, Lenovo, Asus). That contains a desktop-sized Grace Blackwell architecture GPU (GB10), and word on the street is that they're moving into laptops this year. Their market is the same market Apple is pitching the MacBook 5 Pro/Max, too: devs wanting local models. It's not currently a large market, but it's growing quickly. It makes far more sense for Nvidia to build hardware to service this market than to overly focus on their gaming lines. RTX GPUs are sell once. GB-containing consumer devices are "sell once, but then collect recurring revenue when the workloads those developers build hit production on a cloud somewhere."
If I were Nvidia, I would give more attention to consumer GPUs to hedge my bets. When (not if) this AI bubble pops, their AI customers will become worthless to them very quickly as they won't be buying more GPUs. And when that day comes, I would want to still have consumers to sell to, rather than have them all buying from AMD because I ignored them.
the only way this argument works is if AMD somehow creates GPUs that run circles around nvidia and boxes them out price wise, and at the same them themselves don’t start prioritizing enterprise customers more. otherwise consumers will choose the best performing gpu possible, generally people don’t care about companies turning their backs on consumers in this way
I should admit this is partly my personal preference.
That said, gaming has been a durable market for decades, and there’s a strong cycle where better chips enable better games, which then drives more demand for better chips.
> Nvidia should invest more in expanding production capacity
Not if they expect build out of AI data centers to slow down. Once both OpenAI and Anthropic goes public there's going to be a pressure on them to either turn a profit or at least have the stock price go up. One way that can happen, if subscriptions, government contracts and ads aren't working, is cutting back on cost. Cutting costs means doing more with the existing GPUs and datacenters and running them for longer.
Even if the both companies can turn a profit, there's going to be a pressure to not spend on datacenters, if existing facilities can be pushed harder or used more efficiently.
OpenAI and Anthropic going public is going to mean reduced spend on datacenters and GPUs.
nvidia will come back to the consumer side when the AI side stops being as profitable. Right now, it still seems like the margins for AI hardware is way higher than the same consumer product would sell for.
This leaves an opening for Intel to get in the game. Their new lines have a pretty decent value proposition for mid-tier gaming. If they focused on the higher end they would could own it. There is massive latent demand because of the NVidia situation. It’s easier to make money from than the R&D to build the next Blackwell but there is just as much demand for local/private models on the prosumer level.
Nvidia could flip a switch and start competing with former customers. They have the talent, the models, the HW, and they know how to quickly build out DCs.
That would not go well for nvidia. Why would they want to enter and compete in a market where everybody is losing money? And in so doing alienate the people that make them profitable?
They don't, not directly. That's why they've generally been winding down DGX Cloud. However, lots of folks dramatically underestimate their frontier models (Nemotron family), and they license those models (free) for embedding in MANY other, large tech companies' own products and platforms, which either directly or indirectly consume massive quantities of GPU time.
Nvidia is best known for selling huge volumes of GPUs to the hyperscalers & neoclouds, but I don't think lots of folks appreciate how many GPUs ISVs like Snowflake, Databricks, Teradata, etc consume, too, just by virtue of designing much of their internal products around CUDA & Nemotron.
Are you suggesting Nvidia doesn't have talent in the AI industry?
NVIDIA has released NVIDIA Deep Learning Super Sampling (DLSS) and a Frame Generation model, NVIDIA Super Resolution (VSR) being the most popular/well known models. (DLSS is outstanding technology, despite the sometimes misleading marketing).
Nvidia has released countless models:
Alpamayo 1 (Car navigation model)
Cosmos-Reason2 (reasoning vision language model)
Nemotron 3 (Large Language Model series)
Llama-Nemotron (Large Language Model series)
Isaac GR00T (VLA Models)
Nemotron OCR (Optical Character Recognition models)
Take a look at their HuggingFace Collections, almost 100 different collections with countless models inside each collection: https://huggingface.co/nvidia/collections
NV has a massive amount of AI talent, and a lot of them have PhDs.
Are you suggesting they're lacking on the ultra-high-end? That is: 5-10M+ in comp to sign a single researcher/IC; industry rock star territory.
Major frontier AI labs do tend to have that type of talent in abundance. I'm sure NV has the equivalent when it comes to hardware design. Surely in AI research too, but perhaps not in the same quantities.
That's not how a smart business runs and that's now how Nvidia operates.
Jensen is smart. He's gone through over 30 years of tech cycles.
Nvidia actively commoditizes the LLM models. Look at Nemotron. They've avoided making a SOTA model solely to keep the hyperscalers (aka crack addicts) coming back for more GPUs.
As soon as the bubble bursts, they can release some open weight NemoMambaDiffusiontron and keep folks buying GPUs to run the damn thing.
It still wouldn't be smart to do so, as this would fall into the common business pitfall of thinking you could easily do the next stack layer of work.
I don't really understand the idea that not investing more money is a "pullback". Have VC norms propagated so far that any company that makes any investment is presumed to be interested in repeated future rounds?
Blogspam derived from the original article by CNBC, with clickbait title.
> [subtitle] Nvidia CEO Jensen Huang said the company’s recent $30 billion investment in OpenAI “might be the last time” it invests in the AI startup as it gears up to go public.
Jensen meant he expects no more rounds before IPO.
I think it is likely that they realize that LLM models will be able to be developed by many companies, and I see most early, heavy adopters of LLMs doing the math on giving OpenAI/Anthropic token fees versus just having in-house models, and realizing that, at this point, it sure seems like having your own models might be the future path.
Nvidia is in position, and has the resources, to see this with a much broader lens, and realizes OpenAI/Anthropic won't be able to corner the market and the long term play is to sell GPUs to cloud providers and companies themselves.
The article already explains why, both of the companies have taken a huge amount of capital so further investing doesn't make sense and they will both go public soon where they will raise more.
Both companies will need Nvidia products regardless if Nvidia puts capital into the companies. So this is not 'pulling back' as the headline says.
Nvidia sells chips to whoever wins, so investing in a specific lab creates downside with no real upside. The more interesting read is whether Huang sees model providers compressing toward commodity pricing. I wrote about why that layer is structurally squeezed: https://philippdubach.com/posts/is-ai-really-eating-the-worl...
My bet is Nvidia is using massive AI ability to dictate its investments.
And it logically predict that not much (more) investments are needed and it need time to become profitable.
That a signal that nobody should invest more in the IA big companies and now they MUST become profitable soon.
That reads more as an image move. Better of they can position themselves as a provider of neutral tools and stay far away from the DoW discussion on use of said tools
As long as both companies remain stable and viable, there's probably limited upside to pouring more money into them. If they fail, and bring down the AI ecosystem with them, that is very bad news for Nvidia. So they've been there nurturing their success and providing capital to backstop their exponential growth.
You can see Nvidia stepping in throughout the ecosystem with confidence boosting investments where needed. They haven't just supported Anthropic and OpenAI.
If OpenAI and Anthropic succeed, and get their business fly-wheels fully spinning, they don't necessarily need more capital from Huang. Ultimately the goal of Nvidia is to profit from their long-term success by selling them GPUs for a long, long time. The goal isn't to keep plowing money into them forever.
These days Nvidia has more money than it knows what to do with. They could certainly push $5b+ into each company annually and never miss it. They're tracking toward an astounding $200b in operating income (maybe over the next four quarters if the music doesn't suddenly stop).
They could buy back stock or, God forbid, pay good old dividends to investors instead of throwing money away.
Why would paying dividends not be like throwing money away for Nvidia, considering the alternative is to reinvest it into Nvidia's R&D, hiring & training, etc. Investors are already happily making money on NVDA stock appreciation, so what more would they gain from paying dividends?
because of the law of diminishing returns
More money?
5 billion doesn't look like much when OpenAI just raised $110b though. And how sustainable is NVDA's immense profits if this bubble actually bursts?
It did not raise $110 billion. According to their own SEC filings $35 billion of Amazon’s funding is contingent on “(i) OpenAI meeting specified milestones, and (ii) OpenAI directly or indirectly consummating an initial public offering or direct listing of equity securities in the United States”
> 5 billion doesn't look like much when OpenAI just raised $110b though.
Just about all of the AI providers "raises" are a fraction of the reported "raise", like this one.
They didn't "raise" $100b. They got commitments for $35b, with said commitments being dependent on meeting certain criteria.
Every "raise of $FOO" I've seen in the past year or two has not resulted in them getting their hands on $FOO in cash to spend.
You might be surprised to learn that there isn’t even $100b of cash [1]. Some sort of commitment structure necessarily substitutes.
[1]: https://fred.stlouisfed.org/series/USDIVCA
I can hardly believe that this is legal. They’re basically committing money that doesn’t exist just yet.
> I can hardly believe that this is legal. They’re basically committing money that doesn’t exist just yet.
What do you mean "just yet" :-)
I don't really know how likely it is that the money being committed will actually exist when the time comes (Softbank's commitment didn't exist, they had to sell off assets and rope in other investors to meet their commitments).
Maybe it is very likely to exist, but, really, who knows?
IOW, your statement would be equally true by ending the sentence at the word "exist".
would the correct read of this situation that they’re betting on the AI bubble popping?
> would the correct read of this situation that they’re betting on the AI bubble popping?
I really cannot tell. To be frank, I seriously doubt that they can tell either.
Vault cash are actual bills in vaults. It doesn't even include the bills in your wallet or under your mattress.
It's small because few people go to the bank to withdraw a suitcase of $100 bills, it's a weird time series to pull up because it's not really indicative of anything outside of narrow interests for regulators and the mint - it's probably some conspiracy theory trope from crypto bros or something.
Most money exists purely in electronic form these days.
Monetary base [0] which includes the digital money banks have on deposit at the Fed, is over $5 trillion, and even that is tiny compared to M1 [1] which includes the kinds of things backing your money market account, which is around $19T.
When money is invested, they're going to wire it, not pull up with wheelbarrows full of bills.
0. https://fred.stlouisfed.org/series/BOGMBASE 1. https://fred.stlouisfed.org/series/M1SL
GP is wrong though, vault cash is the incorrect time series for that.
GP should have used Monetary Base if they wanted to consider purely electronic cash (that is not a result of any fractional reserve stuff at all), which is over $5T disproving their point.
> When money is invested, they're going to wire it, not pull up with wheelbarrows full of bills.
I think GP was making the point that the "money" doesn't exist even in electronic form.
That's what I was referring to. They're committing money they don't have in any monetary form at all. They're just promising they'll have it when it comes due. This is kind of like MLM.
Doesn't that show physical cash in bank vaults? Am I misunderstanding? That number would be utterly meaningless for this discussion.
Edit: I see this was covered in other replies
If the bubble bursts, having more money in OpenAI is worse for NVDA..
Agreed. I will add NV has product dominance - they don’t need to buy strategic MFN supplier status - why not deploy capital elsewhere?
> Nvidia CEO Jensen Huang said his company’s recent investments in OpenAI and Anthropic are likely to be its last in both, saying that once they go public as anticipated later this year, the opportunity to invest closes
ok, sounds obvious
> Nvidia, for its part, isn’t offering much more on the matter
ok, so no more news from nvidia
> Still, a few other dynamics might also explain the pullback..
Wait it's a pullback?
This is terrible reporting, right?
Almost all reporting is terrible. But yes, this is terrible reporting.
The next round is IPO for both companies. I don't know why the headline is written like that.
Super click baity.
This is several investment rounds in so I think it might be fair to say it's a pullback.
Instead of pouring more money into OpenAI and Anthropic, Nvidia should invest more in expanding production capacity for the RTX 5000 series and future generations. High-end consumer GPU availability is still constrained, especially for the RTX 5090, and street prices remain elevated. Nvidia should come back to the consumer side.
Datacenter income for nVidia last quarter was something like 62B vs the gaming market of <4B. While not quite a rounding error, it feels like the gaming market is just too small for them to put more resources toward it for us consumer folks.
https://nvidianews.nvidia.com/news/nvidia-announces-financia...
It is insanely stupid that '4B' with a B, is 'too small' of an operating space.
The absolute value is irrelevant - it's the opportunity cost that determines this.
It doesn't matter if the consumer market is 4T, if the AI market is 60T!
One strategic reason is to remove oxygen from competitors. Otherwise someone will scoop up the gaming market and put the proceeds into developing technology to compete with NVIDIA in the more lucrative AI space.
I wonder who is going to fill the gaming market if AI market focused companies would simply outbid them during manufacturing? All available and not yet available manufacture is pivoting to AI market
“I wouldn’t pick up $20 if there was $100 on the ground!”
Most people would pick up both.
These economic proclamations don’t seem to make sense, when applied to different contexts — which suggests what you’re saying might be folk wisdom rather than sound theory (and greatly over simplifying the problem).
You’re also discounting ecosystem effects — gaming GPUs driving demand for datacenter and workstation GPUs as hobbyist experimentation turns into industrial usage. We don’t know what would happen if nVidia stopped suppressing the GPU market, because it’s never been tried — nVidia has always viciously undercut their own grassroots.
> “I wouldn’t pick up $20 if there was $100 on the ground!” Most people would pick up both.
No, it’s more like there’s a massive pile of both $20s and $100s on the ground. You wouldn’t waste time running between the two, you’d focus on the $100s
If I have a garbage bag, I'm shoving everything in there.
> Most people would pick up both.
if you're within reach of both, then it's not a choice, and there's no opportunity cost in picking just one - you'd be taking both.
If not within reach of both but just one, and you picking one up means someone else might pick up the other, then which would you choose? The other is then by definition, the opportunity cost.
nVidia is sitting on a huge pile of cash, ie, they’re not constrained by resources — hence the framing as a choice.
cash cannot buy more fabs. ASML machines are the constraint, plus TSMC's capacity is a constraint.
Not to mention that nvidia's cash pile isn't magic - they should not overpay for capacity; they're better off returning cash to investors in that case.
The problem is that Nvidia cannot make infinite amounts of chips so they actually can't pick up both.
You’re standing on a traffic island in the middle of a busy road. The lights change allowing you to cross. On one side there is a $20 note, on the other there is a $100 note. Which side do you go to first?
If you were carrying heavy shopping in both arms would you stop to pick up a quarter?
A dollar?
I wouldn't pick up either even with empty hands. No idea where they've been. Maybe a fiver, a twenty sure. At that point I'd put down my bags and grab both.
But so many gamers want to buy GPUs and can’t because they are sold out or won’t because they are super price inflated. Wouldn’t the gaming market be larger if the products were actually available and at their actual MSRP?
Nvidia can't sell 10x the number of GPUs they sell. As much as the supply issues are discussed, it would likely take them a long time to just double the market. They could try to become the vendor of choice for the PS6/next xbox, but that's a big strategy shift for again maybe double the market, not 10x the market.
On the other hand right now the market doesn't seem to think that the >60bn of datacenter revenue is going away or even going to slow down _growing_ any time soon. Just adding 10% more revenue there is worth more than doubling their GPU business which they likely can't do.
I am not saying it would be anywhere near equal, just that it would be "bigger" than 4B if it wasn't so constrained.
>On the other hand right now the market doesn't seem to think that the >60bn of datacenter revenue is going away or even going to slow down _growing_ any time soon.
I wonder why this then?
https://news.ycombinator.com/item?id=47256781
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No. Enterprise customers generate vastly more revenue and profit than consumers can.
That is not substantiable. AI bubble is wealthy hype like a single drop of blood can be used to validate 100 different diagnostic test. Reality is parts per million fails this along with reusable medium. Wealth latches to idiocy.
Gaming and CAD market are real expectations that latch to reality. Grow the education systems and grow both. So is matrix math, such as hashing.
AI has reached a state of software issue, not hardware. And the divergence of AI hardware does not equate to CAD and Gaming math.
How many of the last ten years have had some kind of "temporary" GPU shortage? It was crypto, now it's LLMs, who knows what's next?
The only winning strategy for these guys is to exploit the market for all it's worth during shortages and carefully control production to manage the inevitable gluts.
> AI has reached a state of software issue, not hardware
Citation very much needed.
At the very least, OpenAI seems to believe more and larger datacenters is the path to better models... and they've been right about that every time so far.
Moreover, all the frontier labs and hyperscalers are capacity constrained, and will be for the foreseeable future.
Their story (valuation) hinges on it - therefore that’s their investment thesis when raising money.
>OpenAI seems to believe more and larger datacenters is the path to better models...
Does that mean they produce better slop, or more slop faster?
Better slop. The effect that these systems get better as you scale up [0] is real you know.
[0]: https://arxiv.org/pdf/2001.08361
Slop is still slop. There is no legitimate evidence that these systems get any better just by throwing more hardware at it. Every one of the people in this paper is involved with OpenAI, so it is very suspect in its findings.
Great, when the AI bubble bursts, they can repackage their AI chips into consumer cards! /s
I am afriad thhe GPUs chips will be often useless (to power hungry, running too hot and needing too expensive accessories) but it might be possible to harvest the memory chips and put them on useful GPU cards.
Why would they do that? They launched the DGX Spark last year with multiple hardware OEMs selling flavors of the reference device (Dell, Lenovo, Asus). That contains a desktop-sized Grace Blackwell architecture GPU (GB10), and word on the street is that they're moving into laptops this year. Their market is the same market Apple is pitching the MacBook 5 Pro/Max, too: devs wanting local models. It's not currently a large market, but it's growing quickly. It makes far more sense for Nvidia to build hardware to service this market than to overly focus on their gaming lines. RTX GPUs are sell once. GB-containing consumer devices are "sell once, but then collect recurring revenue when the workloads those developers build hit production on a cloud somewhere."
And why should a business do that? Limited chip production capacity be spent on most profitable ventures.
You saying they should have gone all in on Crypto mining?
If I were Nvidia, I would give more attention to consumer GPUs to hedge my bets. When (not if) this AI bubble pops, their AI customers will become worthless to them very quickly as they won't be buying more GPUs. And when that day comes, I would want to still have consumers to sell to, rather than have them all buying from AMD because I ignored them.
the only way this argument works is if AMD somehow creates GPUs that run circles around nvidia and boxes them out price wise, and at the same them themselves don’t start prioritizing enterprise customers more. otherwise consumers will choose the best performing gpu possible, generally people don’t care about companies turning their backs on consumers in this way
They don't need to run circles, just be close enough for a good enough price.
Consumer GPUs are too small of a slice of their revenue to matter to them anymore.
Gaming created Nvidia
And now Nvidia is destroying gaming
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I should admit this is partly my personal preference. That said, gaming has been a durable market for decades, and there’s a strong cycle where better chips enable better games, which then drives more demand for better chips.
That same virtuous cycle works for their data center segment
Every GW of Blackwell generates more revenue than the entire gaming business does in 1 year.
> Nvidia should invest more in expanding production capacity
Not if they expect build out of AI data centers to slow down. Once both OpenAI and Anthropic goes public there's going to be a pressure on them to either turn a profit or at least have the stock price go up. One way that can happen, if subscriptions, government contracts and ads aren't working, is cutting back on cost. Cutting costs means doing more with the existing GPUs and datacenters and running them for longer.
Even if the both companies can turn a profit, there's going to be a pressure to not spend on datacenters, if existing facilities can be pushed harder or used more efficiently.
OpenAI and Anthropic going public is going to mean reduced spend on datacenters and GPUs.
nvidia will come back to the consumer side when the AI side stops being as profitable. Right now, it still seems like the margins for AI hardware is way higher than the same consumer product would sell for.
This leaves an opening for Intel to get in the game. Their new lines have a pretty decent value proposition for mid-tier gaming. If they focused on the higher end they would could own it. There is massive latent demand because of the NVidia situation. It’s easier to make money from than the R&D to build the next Blackwell but there is just as much demand for local/private models on the prosumer level.
Fabs are expensive, take decades to make and most important are very hard.
Nvidia designs chips, it has no production capabilities. Most of their chips are produced by TSMC and memory come from SK Hynix.
No problem with that, even if it takes force.
Their model offerings are also need some love.
Nvidia could flip a switch and start competing with former customers. They have the talent, the models, the HW, and they know how to quickly build out DCs.
That would not go well for nvidia. Why would they want to enter and compete in a market where everybody is losing money? And in so doing alienate the people that make them profitable?
They don't, not directly. That's why they've generally been winding down DGX Cloud. However, lots of folks dramatically underestimate their frontier models (Nemotron family), and they license those models (free) for embedding in MANY other, large tech companies' own products and platforms, which either directly or indirectly consume massive quantities of GPU time.
Nvidia is best known for selling huge volumes of GPUs to the hyperscalers & neoclouds, but I don't think lots of folks appreciate how many GPUs ISVs like Snowflake, Databricks, Teradata, etc consume, too, just by virtue of designing much of their internal products around CUDA & Nemotron.
If those customers end up profitable, it could be tempting for nVidia to vertically integrate.
I don't think it's as easy as others say, though.
Presumably Nvidia would have a significant advantage on hardware costs, and could run custom hardware that the rest of the market will never see
And maybe TSMC should make cellphones? If you're higher up the supply chain why go downstream into risk? It's financially irresponsible.
> If you're higher up the supply chain why go downstream into risk? It's financially irresponsible.
Well, classically, to capture more margin for yourself. In business school they call this Vertical Integration. Samsung did exactly this. AWS too.
They don't have the talent.
Are you suggesting Nvidia doesn't have talent in the AI industry?
NVIDIA has released NVIDIA Deep Learning Super Sampling (DLSS) and a Frame Generation model, NVIDIA Super Resolution (VSR) being the most popular/well known models. (DLSS is outstanding technology, despite the sometimes misleading marketing).
Nvidia has released countless models:
Alpamayo 1 (Car navigation model) Cosmos-Reason2 (reasoning vision language model) Nemotron 3 (Large Language Model series) Llama-Nemotron (Large Language Model series) Isaac GR00T (VLA Models) Nemotron OCR (Optical Character Recognition models)
Take a look at their HuggingFace Collections, almost 100 different collections with countless models inside each collection: https://huggingface.co/nvidia/collections
> Are you suggesting Nvidia doesn't have talent in the AI industry?
nVidia has an open position for system architect, orbital station AI datacenter
Sounds like you get to sit on the roof all day looking up.
Parakeet (speech recognition) is also a frontier model
NV has a massive amount of AI talent, and a lot of them have PhDs.
Are you suggesting they're lacking on the ultra-high-end? That is: 5-10M+ in comp to sign a single researcher/IC; industry rock star territory.
Major frontier AI labs do tend to have that type of talent in abundance. I'm sure NV has the equivalent when it comes to hardware design. Surely in AI research too, but perhaps not in the same quantities.
That's not how a smart business runs and that's now how Nvidia operates.
Jensen is smart. He's gone through over 30 years of tech cycles.
Nvidia actively commoditizes the LLM models. Look at Nemotron. They've avoided making a SOTA model solely to keep the hyperscalers (aka crack addicts) coming back for more GPUs.
As soon as the bubble bursts, they can release some open weight NemoMambaDiffusiontron and keep folks buying GPUs to run the damn thing.
It still wouldn't be smart to do so, as this would fall into the common business pitfall of thinking you could easily do the next stack layer of work.
And they have a moat - they can control the quantity and quality of hardware flowing to their competitions?
Competing with your own customers is not a good idea, especially before the bubble pops.
A better headline:
Nvidia rushed some investments in both companies just before they went public and are now are just waiting to get paid.
I don't really understand the idea that not investing more money is a "pullback". Have VC norms propagated so far that any company that makes any investment is presumed to be interested in repeated future rounds?
The Stargate money didn’t show up I guess, and now the whole gridlock is collapsing?
Blogspam derived from the original article by CNBC, with clickbait title.
> [subtitle] Nvidia CEO Jensen Huang said the company’s recent $30 billion investment in OpenAI “might be the last time” it invests in the AI startup as it gears up to go public.
Jensen meant he expects no more rounds before IPO.
[0] https://www.cnbc.com/2026/03/04/nvidia-huang-openai-investme...
I think it is likely that they realize that LLM models will be able to be developed by many companies, and I see most early, heavy adopters of LLMs doing the math on giving OpenAI/Anthropic token fees versus just having in-house models, and realizing that, at this point, it sure seems like having your own models might be the future path.
Nvidia is in position, and has the resources, to see this with a much broader lens, and realizes OpenAI/Anthropic won't be able to corner the market and the long term play is to sell GPUs to cloud providers and companies themselves.
The article already explains why, both of the companies have taken a huge amount of capital so further investing doesn't make sense and they will both go public soon where they will raise more.
Both companies will need Nvidia products regardless if Nvidia puts capital into the companies. So this is not 'pulling back' as the headline says.
Nvidia sells chips to whoever wins, so investing in a specific lab creates downside with no real upside. The more interesting read is whether Huang sees model providers compressing toward commodity pricing. I wrote about why that layer is structurally squeezed: https://philippdubach.com/posts/is-ai-really-eating-the-worl...
My bet is Nvidia is using massive AI ability to dictate its investments. And it logically predict that not much (more) investments are needed and it need time to become profitable.
That a signal that nobody should invest more in the IA big companies and now they MUST become profitable soon.
Or it predicted that they will crash, so they'd better be out before everyone else realizes.
OpenAI and Anthropic are better off with cerebras rather than nvidia
That reads more as an image move. Better of they can position themselves as a provider of neutral tools and stay far away from the DoW discussion on use of said tools
After seeing natural gas prices spike like that I'd probably pull out of such an energy intensive investment too
Perfectly reasonable from Nvidia's side. But now thats one less way for sal altman to engineer the valuation upwards
The important news is that OpenAI and Anthropic are pulling out from NVidia; they are not public companies.
If this AI bubble pops we'll just have a ton of cheap powerful GPUs on the market and possibly even an uptick in job growth in tech.
Everyone knows the bubble is bursting.
Everybody knows that the boat is sinking.
Studies show you stay dry the longest if you stay on the sinking boat.
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